In this study, we analyzed the effects of motorcycle riders' emotional states and human characteristics on their lane change behavior. As a result, we confirmed that motorcycle riders tend to change lanes when the valence level of Russell's emotion model is negative, even in risky situations with small time to collision (TTC) with the following vehicle in the adjacent lane. We also clarified indicators of human characteristics related to the lane change behavior of motorcycle riders. Finally, we constructed a model to estimate the lane change probability of a motorcycle rider using their emotional states, human characteristics, and surrounding vehicle information based on logistic regression analysis in order to propose a cooperative Human-Machine Interface (HMI) for two-wheeled and four-wheeled vehicles.

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This study investigated a screening method for assessing driving ability in participants aged ≥65 years, focusing on physical function, specifically handgrip strength (HGS). Quantitative validation analysis revealed a negative correlation between HGS and age and a weak positive correlation between rate of change in HGS and driving simulator score change. The accident rate was slightly higher among individuals with low HGS, though further validation is necessary. Additionally, qualitative validation highlighted individual differences influenced by exercise frequency and social participation. Consequently, we recommend that evaluation methods consider these individual variations, especially when assessing driving ability in individuals with lower HGS.

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